AI Coach - Tester

Clurgo is a company created by developers for developers. Their teams cover a full spectrum of competencies — from software development and infrastructure, through analysis and testing, to strategic product and process management. They execute diverse IT projects for clients from many industries, maintaining good programming practices and work-life balance. They create solutions meaningful for companies in Poland and worldwide.

• 6+ years of experience in IT with a strong background in automated testing (including Selenium, Postman, Jenkins) and excellent knowledge of SDLC processes
• Practical experience with classical QA stack and automation tools: Selenium, Jenkins, Postman, JMeter, SQL, and code and log management tools (GitHub, Bitbucket, Kibana)
• Excellent familiarity with modern AI ecosystem, including handling LLMs (ChatGPT, Claude, oLlama) and developer assistants (GitHub Copilot Chat, M365 Copilot)
• Advanced skills in building effective prompts and optimizing workflows
• Experience in conducting trainings, workshops, or internal mentoring in IT/modern technologies and willingness to share knowledge

Nice to have:

• Experience with advanced AI technologies and architectures: LangChain, RAG, AI Gateway, MLOps, Hugging Face
• Knowledge of cloud environments, especially Azure (Azure OpenAI, Azure AI Foundry) and Google Cloud Platform
• Knowledge in AI Governance, AI Act, and working with unstructured documents in highly regulated environments
• Practical knowledge of Python and related frameworks (FastAPI, Flask) and containerization tools (Docker, Kubernetes)
• Higher education in computer science or related fields

• Leading AI implementations in the software development lifecycle (SDLC): needs analysis, configuration, usage standards, policy and governance, and scaling
• Supporting testers and development teams in using AI tools (e.g., GitHub Copilot, Claude Code) including selecting appropriate models for tasks
• Assisting testers in building efficient prompts and optimizing daily workflows
• Conducting trainings, workshops, and ongoing consultations for IT teams
• Creating an internal knowledge base and best practices for AI usage
• Defining and measuring KPIs, OKRs, and ROI of AI implementations (productivity, quality, costs) and reporting results to IT stakeholders
• Coordinating and monitoring AI-related initiatives and implementing real changes in the development process
• Comparing market solutions (e.g., GitHub Copilot Chat, M365 Copilot vs alternatives) and issuing recommendations based on quality, cost, risk, and compliance